Full Job Description
We are looking for a talented Business Intelligence Engineer to join the Manufacturing Operations, Transportation Operations, and Reverse (MOTOR) organization in support of our Supply Chain Intelligence team. MOTOR manages the manufacturing of datacenter racks and the movement of racks/parts through the supply chain, consisting of transportation, warehousing, and reverse logistics into and out of the data centers. This role requires someone with strong analytic skills and business acumen who will work with stakeholders on strategic projects within MOTOR.
The ideal candidate must be able to identify problems before they happen and implement solutions that detect and prevent outages. The candidate must be able to accurately prioritize projects, make sound judgments, work to improve the customer experience and get the right things done. Technical ability to support dashboard creation supporting daily operations, track KPIs, and provide holistic performance measurements to be shared with internal and external stakeholders is desired. The role plays a critical part in ensuring strategic commitments are made and operations are exceeding desired performance levels by using metrics to drive accountability and process improvements.
Key job responsibilities
- Build reports, dashboards, and analyses to deliver metrics and insights to the business.
- Translate difficult business problem statements into analysis requirements and maintain high bar throughout the execution.
- Define analytical approach; review and vet analytical approach with stakeholders.
- Proactively and independently work with stakeholders to construct use cases and associated standardized outputs.
- Have a working knowledge of the data available or needed by the wider business for more complex or comparative analysis.
- Report key insight trends, using statistical rigor to simplify and inform the larger team of noteworthy story lines that impact the business.
- Learn and understand a broad range of Amazon's data resources and know how, when, and which
About the team
This team provides data engineering and business intelligence engineering services to the rest of MOTOR. We are the data experts behind the scenes helping the operational teams focus on operations by ensuring they have accurate, timely data and provide business insights to help improve operational excellence.
BASIC QUALIFICATIONS
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 1+ years of SQL, ETL or Oracle experience
- 1+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 1+ years of developing automated reporting experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
PREFERRED QUALIFICATIONS
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Arlington - 99,500.00 - 160,000.00 USD annually
USA, WA, Bellevue - 99,500.00 - 160,000.00 USD annually
